Feedback generates a second receptive field in neurons of the visual cortex

Animals sense the environment through pathways that link sensory organs to the brain. In the visual system, these feedforward pathways define the classical feedforward receptive field (ffRF), the area in space in which visual stimuli excite a neuron1. The visual system also uses visual context-the visual scene surrounding a stimulus-to predict the content of the stimulus2, and accordingly, neurons have been identified that are excited by stimuli outside their ffRF3-8. However, the mechanisms that generate excitation to stimuli outside the ffRF are unclear. Here we show that feedback projections onto excitatory neurons in the mouse primary visual cortex generate a second receptive field that is driven by stimuli outside the ffRF. The stimulation of this feedback receptive field (fbRF) elicits responses that are slower and are delayed in comparison with those resulting from the stimulation of the ffRF. These responses are preferentially reduced by anaesthesia and by silencing higher visual areas. Feedback inputs from higher visual areas have scattered receptive fields relative to their putative targets in the primary visual cortex, which enables the generation of the fbRF. Neurons with fbRFs are located in cortical layers that receive strong feedback projections and are absent in the main input layer, which is consistent with a laminar processing hierarchy. The observation that large, uniform stimuli-which cover both the fbRF and the ffRF-suppress these responses indicates that the fbRF and the ffRF are mutually antagonistic. Whereas somatostatin-expressing inhibitory neurons are driven by these large stimuli, inhibitory neurons that express parvalbumin and vasoactive intestinal peptide have mutually antagonistic fbRF and ffRF, similar to excitatory neurons. Feedback projections may therefore enable neurons to use context to estimate information that is missing from the ffRF and to report differences in stimulus features across visual space, regardless of whether excitation occurs inside or outside the ffRF. By complementing the ffRF, the fbRF that we identify here could contribute to predictive processing.

Anatomy and Physiology of Macaque Visual Cortical Areas V1, V2, and V5/MT: Bases for Biologically Realistic Models

The cerebral cortex of primates encompasses multiple anatomically and physiologically distinct areas processing visual information. Areas V1, V2, and V5/MT are conserved across mammals and are central for visual behavior. To facilitate the generation of biologically accurate computational models of primate early visual processing, here we provide an overview of over 350 published studies of these three areas in the genus Macaca, whose visual system provides the closest model for human vision. The literature reports 14 anatomical connection types from the lateral geniculate nucleus of the thalamus to V1 having distinct layers of origin or termination, and 194 connection types between V1, V2, and V5, forming multiple parallel and interacting visual processing streams. Moreover, within V1, there are reports of 286 and 120 types of intrinsic excitatory and inhibitory connections, respectively. Physiologically, tuning of neuronal responses to 11 types of visual stimulus parameters has been consistently reported. Overall, the optimal spatial frequency (SF) of constituent neurons decreases with cortical hierarchy. Moreover, V5 neurons are distinct from neurons in other areas for their higher direction selectivity, higher contrast sensitivity, higher temporal frequency tuning, and wider SF bandwidth. We also discuss currently unavailable data that could be useful for biologically accurate models.

Integrative analysis of in vivo recording with single-cell RNA-seq data reveals molecular properties of light-sensitive neurons in mouse V1

Vision formation is classically based on projections from retinal ganglion cells (RGC) to the lateral geniculate nucleus (LGN) and the primary visual cortex (V1). Neurons in the mouse V1 are tuned to light stimuli. Although the cellular information of the retina and the LGN has been widely studied, the transcriptome profiles of single light-stimulated neuron in V1 remain unknown. In our study, in vivo calcium imaging and whole-cell electrophysiological patch-clamp recording were utilized to identify 53 individual cells from layer 2/3 of V1 as light-sensitive (LS) or non-light-sensitive (NS) by single-cell light-evoked calcium evaluation and action potential spiking. The contents of each cell after functional tests were aspirated in vivo through a patch-clamp pipette for mRNA sequencing. Moreover, the three-dimensional (3-D) morphological characterizations of the neurons were reconstructed in a live mouse after the whole-cell recordings. Our sequencing results indicated that V1 neurons with a high expression of genes related to transmission regulation, such as Rtn4r and Rgs7, and genes involved in membrane transport, such as Na⁺/K⁺ ATPase and NMDA-type glutamatergic receptors, preferentially responded to light stimulation. Furthermore, an antagonist that blocks Rtn4r signals could inactivate the neuronal responses to light stimulation in live mice. In conclusion, our findings of the vivo-seq analysis indicate the key role of the strength of synaptic transmission possesses neurons in V1 of light sensory.

Inference of nonlinear receptive field subunits with spike-triggered clustering

Responses of sensory neurons are often modeled using a weighted combination of rectified linear subunits. Since these subunits often cannot be measured directly, a flexible method is needed to infer their properties from the responses of downstream neurons. We present a method for maximum likelihood estimation of subunits by soft-clustering spike-triggered stimuli, and demonstrate its effectiveness in visual neurons. For parasol retinal ganglion cells in macaque retina, estimated subunits partitioned the receptive field into compact regions, likely representing aggregated bipolar cell inputs. Joint clustering revealed shared subunits between neighboring cells, producing a parsimonious population model. Closed-loop validation, using stimuli lying in the null space of the linear receptive field, revealed stronger nonlinearities in OFF cells than ON cells. Responses to natural images, jittered to emulate fixational eye movements, were accurately predicted by the subunit model. Finally, the generality of the approach was demonstrated in macaque V1 neurons.

Lamina-specific AMPA receptor dynamics following visual deprivation in vivo

Regulation of AMPA receptor (AMPAR) expression is central to synaptic plasticity and brain function, but how these changes occur in vivo remains elusive. Here, we developed a method to longitudinally monitor the expression of synaptic AMPARs across multiple cortical layers in awake mice using two-photon imaging. We observed that baseline AMPAR expression in individual spines is highly dynamic with more dynamics in primary visual cortex (V1) layer 2/3 (L2/3) neurons than V1 L5 neurons. Visual deprivation through binocular enucleation induces a synapse-specific and depth-dependent change of synaptic AMPARs in V1 L2/3 neurons, wherein deep synapses are potentiated more than superficial synapses. The increase is specific to L2/3 neurons and absent on apical dendrites of L5 neurons, and is dependent on expression of the AMPAR-binding protein GRIP1. Our study demonstrates that specific neuronal connections, across cortical layers and even within individual neurons, respond uniquely to changes in sensory experience.

Natural images are reliably represented by sparse and variable populations of neurons in visual cortex

Natural scenes sparsely activate neurons in the primary visual cortex (V1). However, how sparsely active neurons reliably represent complex natural images and how the information is optimally decoded from these representations have not been revealed. Using two-photon calcium imaging, we recorded visual responses to natural images from several hundred V1 neurons and reconstructed the images from neural activity in anesthetized and awake mice. A single natural image is linearly decodable from a surprisingly small number of highly responsive neurons, and the remaining neurons even degrade the decoding. Furthermore, these neurons reliably represent the image across trials, regardless of trial-to-trial response variability. Based on our results, diverse, partially overlapping receptive fields ensure sparse and reliable representation. We suggest that information is reliably represented while the corresponding neuronal patterns change across trials and collecting only the activity of highly responsive neurons is an optimal decoding strategy for the downstream neurons.

Effect of interphase gap duration and stimulus rate on threshold of visual cortical neurons in the rat

Stimulation threshold is a key parameter to enable an efficient design for retinal implants. Stimulation parameters such as stimulus pulse duration, pulse amplitude, pulse repetition, pulse shape and polarity have been shown to be the key factors that can influence the efficacy of retinal prosthetics. The effectiveness of these devices should best be evaluated both in the retina and in the visual cortex. Prior electrophysiological studies in the retina have shown that introducing an interphase gap make stimulation more efficient. Previous in vitro studies have also demonstrated the response properties of retinal ganglion cells are frequency dependent. However, the effect of these two stimulus parameters are not well explored at the cortical level where higher visual processing signals are processed. In this study, we examined the response properties of visual cortical neurons under stimulation of retinal ganglion cells in rat using a single-channel electrode of diameter 75 μm. We compared the response strength curves as a function of stimulus current amplitudes under different stimulus pulse duration, interphase gap and stimulus rate. Localized response to single channel epiretinal stimulation was robustly observed in V1 neurons. We found that V1 neurons were more sensitive to longer pulse and stimulus with an interphase gap, similar to previously reported results in the retina. We were also able to examine the effect of stimulus frequency on threshold in the visual cortex. Our results indicate that electrical activation of V1 neurons are more efficient at low frequency.

Dopamine Receptor Expression Among Local and Visual Cortex-Projecting Frontal Eye Field Neurons

Dopaminergic modulation of prefrontal cortex plays an important role in numerous cognitive processes, including attention. The frontal eye field (FEF) is modulated by dopamine and has an established role in visual attention, yet the underlying circuitry upon which dopamine acts is not known. We compared the expression of D1 and D2 dopamine receptors (D1Rs and D2Rs) across different classes of FEF neurons, including those projecting to dorsal or ventral extrastriate cortex. First, we found that both D1Rs and D2Rs are more prevalent on pyramidal neurons than on several classes of interneurons and are particularly prevalent on putatively long-range projecting pyramidals. Second, higher proportions of pyramidal neurons express D1Rs than D2Rs. Third, overall a higher proportion of inhibitory neurons expresses D2Rs than D1Rs. Fourth, among inhibitory interneurons, a significantly higher proportion of parvalbumin+ neurons expresses D2Rs than D1Rs, and a significantly higher proportion of calbindin+ neurons expresses D1Rs than D2Rs. Finally, compared with D2Rs, virtually all of the neurons with identified projections to both dorsal and ventral extrastriate visual cortex expressed D1Rs. Our results demonstrate that dopamine tends to act directly on the output of the FEF and that dopaminergic modulation of top-down projections to visual cortex is achieved predominately via D1Rs.

Temporal information loss in the macaque early visual system

Stimuli that modulate neuronal activity are not always detectable, indicating a loss of information between the modulated neurons and perception. To identify where in the macaque visual system information about periodic light modulations is lost, signal-to-noise ratios were compared across simulated cone photoreceptors, lateral geniculate nucleus (LGN) neurons, and perceptual judgements. Stimuli were drifting, threshold-contrast Gabor patterns on a photopic background. The sensitivity of LGN neurons, extrapolated to populations, was similar to the monkeys' at low temporal frequencies. At high temporal frequencies, LGN sensitivity exceeded the monkeys' and approached the upper bound set by cone photocurrents. These results confirm a loss of high-frequency information downstream of the LGN. However, this loss accounted for only about 5% of the total. Phototransduction accounted for essentially all of the rest. Together, these results show that low temporal frequency information is lost primarily between the cones and the LGN, whereas high-frequency information is lost primarily within the cones, with a small additional loss downstream of the LGN.

Recurrent interactions can explain the variance in single trial responses

To develop a complete description of sensory encoding, it is necessary to account for trial-to-trial variability in cortical neurons. Using a linear model with terms corresponding to the visual stimulus, mouse running speed, and experimentally measured neuronal correlations, we modeled short term dynamics of L2/3 murine visual cortical neurons to evaluate the relative importance of each factor to neuronal variability within single trials. We find single trial predictions improve most when conditioning on the experimentally measured local correlations in comparison to predictions based on the stimulus or running speed. Specifically, accurate predictions are driven by positively co-varying and synchronously active functional groups of neurons. Including functional groups in the model enhances decoding accuracy of sensory information compared to a model that assumes neuronal independence. Functional groups, in encoding and decoding frameworks, provide an operational definition of Hebbian assemblies in which local correlations largely explain neuronal responses on individual trials.

Contribution of apical and basal dendrites to orientation encoding in mouse V1 L2/3 pyramidal neurons

Pyramidal neurons integrate synaptic inputs from basal and apical dendrites to generate stimulus-specific responses. It has been proposed that feed-forward inputs to basal dendrites drive a neuron's stimulus preference, while feedback inputs to apical dendrites sharpen selectivity. However, how a neuron's dendritic domains relate to its functional selectivity has not been demonstrated experimentally. We performed 2-photon dendritic micro-dissection on layer-2/3 pyramidal neurons in mouse primary visual cortex. We found that removing the apical dendritic tuft did not alter orientation-tuning. Furthermore, orientation-tuning curves were remarkably robust to the removal of basal dendrites: ablation of 2 basal dendrites was needed to cause a small shift in orientation preference, without significantly altering tuning width. Computational modeling corroborated our results and put limits on how orientation preferences among basal dendrites differ in order to reproduce the post-ablation data. In conclusion, neuronal orientation-tuning appears remarkably robust to loss of dendritic input.

Xenotransplanted Human Cortical Neurons Reveal Species-Specific Development and Functional Integration into Mouse Visual Circuits

How neural circuits develop in the human brain has remained almost impossible to study at the neuronal level. Here, we investigate human cortical neuron development, plasticity, and function using a mouse/human chimera model in which xenotransplanted human cortical pyramidal neurons integrate as single cells into the mouse cortex. Combined neuronal tracing, electrophysiology, and in vivo structural and functional imaging of the transplanted cells reveal a coordinated developmental roadmap recapitulating key milestones of human cortical neuron development. The human neurons display a prolonged developmental timeline, indicating the neuron-intrinsic retention of juvenile properties as an important component of human brain neoteny. Following maturation, human neurons in the visual cortex display tuned, decorrelated responses to visual stimuli, like mouse neurons, demonstrating their capacity for physiological synaptic integration in host cortical circuits. These findings provide new insights into human neuronal development and open novel avenues for the study of human neuronal function and disease.

Video Abstract

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Cell-intrinsic mechanisms of human neoteny in mouse-human chimeric cerebral cortex

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Human neurons show prolonged maturation and single-cell integration in mouse cortex

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Stable dendritic spines and long-term synaptic plasticity in xenotransplanted neurons

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Human neurons show decorrelated activity and tuned responses to visual stimuli

The geometry of masking in neural populations

The normalization model provides an elegant account of contextual modulation in individual neurons of primary visual cortex. Understanding the implications of normalization at the population level is hindered by the heterogeneity of cortical neurons, which differ in the composition of their normalization pools and semi-saturation constants. Here we introduce a geometric approach to investigate contextual modulation in neural populations and study how the representation of stimulus orientation is transformed by the presence of a mask. We find that population responses can be embedded in a low-dimensional space and that an affine transform can account for the effects of masking. The geometric analysis further reveals a link between changes in discriminability and bias induced by the mask. We propose the geometric approach can yield new insights into the image processing computations taking place in early visual cortex at the population level while coping with the heterogeneity of single cell behavior.

Integration of cortical population signals for visual perception

Visual stimuli evoke heterogeneous responses across nearby neural populations. These signals must be locally integrated to contribute to perception, but the principles underlying this process are unknown. Here, we exploit the systematic organization of orientation preference in macaque primary visual cortex (V1) and perform causal manipulations to examine the limits of signal integration. Optogenetic stimulation and visual stimuli are used to simultaneously drive two neural populations with overlapping receptive fields. We report that optogenetic stimulation raises firing rates uniformly across conditions, but improves the detection of visual stimuli only when activating cells that are preferentially-tuned to the visual stimulus. Further, we show that changes in correlated variability are exclusively present when the optogenetically and visually-activated populations are functionally-proximal, suggesting that correlation changes represent a hallmark of signal integration. Our results demonstrate that information from functionally-proximal neurons is pooled for perception, but functionally-distal signals remain independent.

Close Homolog of L1 Regulates Dendritic Spine Density in the Mouse Cerebral Cortex Through Semaphorin 3B

Dendritic spines in the developing mammalian neocortex are initially overproduced and then eliminated during adolescence to achieve appropriate levels of excitation in mature networks. We show here that the L1 family cell adhesion molecule Close Homolog of L1 (CHL1) and secreted repellent ligand Semaphorin 3B (Sema3B) function together to induce dendritic spine pruning in developing cortical pyramidal neurons. Loss of CHL1 in null mutant mice in both genders resulted in increased spine density and a greater proportion of immature spines on apical dendrites in the prefrontal and visual cortex. Electron microscopy showed that excitatory spine synapses with postsynaptic densities were increased in the CHL1-null cortex, and electrophysiological recording in prefrontal slices from mutant mice revealed deficiencies in excitatory synaptic transmission. Mechanistically, Sema3B protein induced elimination of spines on apical dendrites of cortical neurons cultured from wild-type but not CHL1-null embryos. Sema3B was secreted by the cortical neuron cultures, and its levels increased when cells were treated with the GABA antagonist gabazine. In vivo CHL1 was coexpressed with Sema3B in pyramidal neuron subpopulations and formed a complex with Sema3B receptor subunits Neuropilin-2 and PlexinA4. CHL1 and NrCAM, a closely related L1 adhesion molecule, localized primarily to distinct spines and promoted spine elimination to Sema3B or Sema3F, respectively. These results support a new concept in which selective spine elimination is achieved through different secreted semaphorins and L1 family adhesion molecules to sculpt functional neural circuits during postnatal maturation.SIGNIFICANCE STATEMENT Dendritic spines in the mammalian neocortex are initially overproduced and then pruned in adolescent life through unclear mechanisms to sculpt maturing cortical circuits. Here, we show that spine and excitatory synapse density of pyramidal neurons in the developing neocortex is regulated by the L1 adhesion molecule, Close Homolog of L1 (CHL1). CHL1 mediated spine pruning in response to the secreted repellent ligand Semaphorin 3B and associated with receptor subunits Neuropilin-2 and PlexinA4. CHL1 and related L1 adhesion molecule NrCAM localized to distinct spines, and promoted spine elimination to Semaphorin 3B and -3F, respectively. These results support a new concept in which selective elimination of individual spines and nascent synapses can be achieved through the action of distinct secreted semaphorins and L1 adhesion molecules.

Information processing in the LGN: a comparison of neural codes and cell types

To understand how anatomy and physiology allow an organism to perform its function, it is important to know how information that is transmitted by spikes in the brain is received and encoded. A natural question is whether the spike rate alone encodes the information about a stimulus (rate code), or additional information is contained in the temporal pattern of the spikes (temporal code). Here we address this question using data from the cat Lateral Geniculate Nucleus (LGN), which is the visual portion of the thalamus, through which visual information from the retina is communicated to the visual cortex. We analyzed the responses of LGN neurons to spatially homogeneous spots of various sizes with temporally random luminance modulation. We compared the Firing Rate with the Shannon Information Transmission Rate , which quantifies the information contained in the temporal relationships between spikes. We found that the behavior of these two rates can differ quantitatively. This suggests that the energy used for spiking does not translate directly into the information to be transmitted. We also compared Firing Rates with Information Rates for X-ON and X-OFF cells. We found that, for X-ON cells the Firing Rate and Information Rate often behave in a completely different way, while for X-OFF cells these rates are much more highly correlated. Our results suggest that for X-ON cells a more efficient "temporal code" is employed, while for X-OFF cells a straightforward "rate code" is used, which is more reliable and is correlated with energy consumption.

Laminar segregation of sensory coding and behavioral readout in macaque V4

Neurons in sensory areas of the neocortex are known to represent information both about sensory stimuli and behavioral state, but how these 2 disparate signals are integrated across cortical layers is poorly understood. To study this issue, we measured the coding of visual stimulus orientation and of behavioral state by neurons within superficial and deep layers of area V4 in monkeys while they covertly attended or prepared eye movements to visual stimuli. We show that whereas single neurons and neuronal populations in the superficial layers conveyed more information about the orientation of visual stimuli than neurons in deep layers, the opposite was true of information about the behavioral relevance of those stimuli. In particular, deep layer neurons encoded greater information about the direction of planned eye movements than superficial neurons. These results suggest a division of labor between cortical layers in the coding of visual input and visually guided behavior.

Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq

Identifying gene expression programs underlying both cell-type identity and cellular activities (e.g. life-cycle processes, responses to environmental cues) is crucial for understanding the organization of cells and tissues. Although single-cell RNA-Seq (scRNA-Seq) can quantify transcripts in individual cells, each cell's expression profile may be a mixture of both types of programs, making them difficult to disentangle. Here, we benchmark and enhance the use of matrix factorization to solve this problem. We show with simulations that a method we call consensus non-negative matrix factorization (cNMF) accurately infers identity and activity programs, including their relative contributions in each cell. To illustrate the insights this approach enables, we apply it to published brain organoid and visual cortex scRNA-Seq datasets; cNMF refines cell types and identifies both expected (e.g. cell cycle and hypoxia) and novel activity programs, including programs that may underlie a neurosecretory phenotype and synaptogenesis.

High-dimensional geometry of population responses in visual cortex

A neuronal population encodes information most efficiently when its stimulus responses are high-dimensional and uncorrelated, and most robustly when they are lower-dimensional and correlated. Here we analysed the dimensionality of the encoding of natural images by large populations of neurons in the visual cortex of awake mice. The evoked population activity was high-dimensional, and correlations obeyed an unexpected power law: the nth principal component variance scaled as 1/n. This scaling was not inherited from the power law spectrum of natural images, because it persisted after stimulus whitening. We proved mathematically that if the variance spectrum was to decay more slowly then the population code could not be smooth, allowing small changes in input to dominate population activity. The theory also predicts larger power-law exponents for lower-dimensional stimulus ensembles, which we validated experimentally. These results suggest that coding smoothness may represent a fundamental constraint that determines correlations in neural population codes.

Classification of electrophysiological and morphological neuron types in the mouse visual cortex

Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To systematically profile morpho-electric properties of mammalian neurons, we established a single-cell characterization pipeline using standardized patch-clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly accessible online database, the Allen Cell Types Database, to display these datasets. Intrinsic physiological properties were measured from 1,938 neurons from the adult laboratory mouse visual cortex, morphological properties were measured from 461 reconstructed neurons, and 452 neurons had both measurements available. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We established a taxonomy of morphologically and electrophysiologically defined cell types for this region of the cortex, with 17 electrophysiological types, 38 morphological types and 46 morpho-electric types. There was good correspondence with previously defined transcriptomic cell types and subclasses using the same transgenic mouse lines.

p75 Neurotrophin Receptor Activation Regulates the Timing of the Maturation of Cortical Parvalbumin Interneuron Connectivity and Promotes Juvenile-like Plasticity in Adult Visual Cortex

By virtue of their extensive axonal arborization and perisomatic synaptic targeting, cortical inhibitory parvalbumin (PV) cells strongly regulate principal cell output and plasticity and modulate experience-dependent refinement of cortical circuits during development. An interesting aspect of PV cell connectivity is its prolonged maturation time course, which is completed only by end of adolescence. The p75 neurotrophin receptor (p75NTR) regulates numerous cellular functions; however, its role on cortical circuit development and plasticity remains elusive, mainly because localizing p75NTR expression with cellular and temporal resolution has been challenging. By using RNAscope and a modified version of the proximity ligation assay, we found that p75NTR expression in PV cells decreases between the second and fourth postnatal week, at a time when PV cell synapse numbers increase dramatically. Conditional knockout of p75NTR in single PV neurons in vitro and in PV cell networks in vivo causes precocious formation of PV cell perisomatic innervation and perineural nets around PV cell somata, therefore suggesting that p75NTR expression modulates the timing of maturation of PV cell connectivity in the adolescent cortex. Remarkably, we found that PV cells still express p75NTR in adult mouse cortex of both sexes and that its activation is sufficient to destabilize PV cell connectivity and to restore cortical plasticity following monocular deprivation in vivo Together, our results show that p75NTR activation dynamically regulates PV cell connectivity, and represent a novel tool to foster brain plasticity in adults.SIGNIFICANCE STATEMENT In the cortex, inhibitory, GABA-releasing neurons control the output and plasticity of excitatory neurons. Within this diverse group, parvalbumin-expressing (PV) cells form the larger inhibitory system. PV cell connectivity develops slowly, reaching maturity only at the end of adolescence; however, the mechanisms controlling the timing of its maturation are not well understood. We discovered that the expression of the neurotrophin receptor p75NTR in PV cells inhibits the maturation of their connectivity in a cell-autonomous fashion, both in vitro and in vivo, and that p75NTR activation in adult PV cells promotes their remodeling and restores cortical plasticity. These results reveal a new p75NTR function in the regulation of the time course of PV cell maturation and in limiting cortical plasticity.

Leucine-rich repeat kinase 2 (LRRK2) inhibitors differentially modulate glutamate release and Serine935 LRRK2 phosphorylation in striatal and cerebrocortical synaptosomes

Mutations in leucine-rich repeat kinase 2 (LRRK2) gene have been pathogenically linked to Parkinson's disease, and pharmacological inhibition of LRRK2 is being pursued to tackle nigro-striatal dopaminergic neurodegeneration. However, LRRK2 kinase inhibitors may have manifold actions, affecting not only pathological mechanisms in dopaminergic neurons but also physiological functions in nondopaminergic neurons. Therefore, we investigated whether LRRK2 kinase inhibitors differentially modulate dopamine and glutamate release from the mouse striatum and cerebral cortex. Spontaneous and KCl-evoked [3H]-dopamine and glutamate release from superfused synaptosomes obtained from wild-type and LRRK2 knock-out, kinase-dead or G2019S knock-in mice was measured. Two structurally unrelated inhibitors, LRRK2-IN-1 and GSK2578215A, were tested. LRRK2, phosphoSerine1292 and phosphoSerine935 LRRK2 levels were measured in all genotypes, and target engagement was evaluated by monitoring phosphoSerine935 LRRK2. LRRK2-IN-1 inhibited striatal glutamate but not dopamine release; GSK2578215A inhibited striatal dopamine and cortical glutamate but enhanced striatal glutamate release. LRRK2-IN-1 reduced striatal and cortical phosphoSerine935 levels whereas GSK2578215A inhibited only the former. Neither LRRK2 inhibitor affected neurotransmitter release in LRRK2 knock-out and kinase-dead mice; however, they facilitated dopamine without affecting striatal glutamate in G2019S knock-in mice. GSK2578215A inhibited cortical glutamate release in G2019S knock-in mice. We conclude that LRRK2-IN-1 and GSK2578215A modulate exocytosis by blocking LRRK2 kinase activity, although their effects vary depending on the nerve terminal examined. The G2019S mutation unravels a dopamine-promoting action of LRRK2 inhibitors while blunting their effects on glutamate release, which highlights their positive potential for the treatment of PD, especially of LRRK2 mutation carriers.

Transcriptomic correlates of electrophysiological and morphological diversity within and across excitatory and inhibitory neuron classes

In order to further our understanding of how gene expression contributes to key functional properties of neurons, we combined publicly accessible gene expression, electrophysiology, and morphology measurements to identify cross-cell type correlations between these data modalities. Building on our previous work using a similar approach, we distinguished between correlations which were "class-driven," meaning those that could be explained by differences between excitatory and inhibitory cell classes, and those that reflected graded phenotypic differences within classes. Taking cell class identity into account increased the degree to which our results replicated in an independent dataset as well as their correspondence with known modes of ion channel function based on the literature. We also found a smaller set of genes whose relationships to electrophysiological or morphological properties appear to be specific to either excitatory or inhibitory cell types. Next, using data from PatchSeq experiments, allowing simultaneous single-cell characterization of gene expression and electrophysiology, we found that some of the gene-property correlations observed across cell types were further predictive of within-cell type heterogeneity. In summary, we have identified a number of relationships between gene expression, electrophysiology, and morphology that provide testable hypotheses for future studies.

Two-Color Volumetric Imaging of Neuronal Activity of Cortical Columns

To capture the emergent properties of neural circuits, high-speed volumetric imaging of neural activity at cellular resolution is needed. Here, we introduce wavelength multiplexing to perform fast volumetric two-photon imaging of cortical columns (>2,000 neurons in 10 planes at 10 vol/s), using two different calcium indicators, an electrically tunable lens and a spatial light modulator. We image the activity of neuronal populations from layers 2/3 to 5 of primary visual cortex from awake mice, finding a lack of columnar structures in orientation responses and revealing correlations between layers which differ from trial to trial. We also simultaneously image functional correlations between presynaptic layer 1 axons and postsynaptic layer 2/3 neurons. Wavelength multiplexing enhances high-speed volumetric microscopy and can be combined with other optical multiplexing methods to easily boost imaging throughput.

V1 microcircuit dynamics: altered signal propagation suggests intracortical origins for adaptation in response to visual repetition

Repetitive visual stimulation profoundly changes sensory processing in the primary visual cortex (V1). We show how the associated adaptive changes are linked to an altered flow of synaptic activation across the V1 laminar microcircuit. Using repeated visual stimulation, we recorded layer-specific responses in V1 of two fixating monkeys. We found that repetition-related spiking suppression was most pronounced outside granular V1 layers that receive the main retinogeniculate input. This repetition-related response suppression was robust to alternating stimuli between the eyes, in line with the notion that repetition-related adaptation is predominantly of cortical origin. Most importantly, current source density (CSD) analysis, which provides an estimate of local net depolarization, revealed that synaptic processing during repeated stimulation was most profoundly affected within supragranular layers, which harbor the bulk of cortico-cortical connections. Direct comparison of the temporal evolution of laminar CSD and spiking activity showed that stimulus repetition first affected supragranular synaptic currents, which translated into a reduction of stimulus-evoked spiking across layers. Together, these results suggest that repetition induces an altered state of intracortical processing that underpins visual adaptation. NEW & NOTEWORTHY Our survival depends on our brains rapidly adapting to ever changing environments. A well-studied form of adaptation occurs whenever we encounter the same or similar stimuli repeatedly. We show that this repetition-related adaptation is supported by systematic changes in the flow of sensory activation across the laminar cortical microcircuitry of primary visual cortex. These results demonstrate how adaptation impacts neuronal interactions across cortical circuits.

Densities and Laminar Distributions of Kv3.1b-, PV-, GABA-, and SMI-32-Immunoreactive Neurons in Macaque Area V1

The Kv3.1b potassium channel subunit is associated with narrow spike widths and fast-spiking properties. In macaque primary visual cortex (V1), subsets of neurons have previously been found to be Kv3.1b-immunoreactive (ir) but not parvalbumin (PV)-ir or not GABA-ir, suggesting that they may be both fast-spiking and excitatory. This population includes Meynert cells, the large layer 5/6 pyramidal neurons that are also labeled by the neurofilament antibody SMI-32. In the present study, triple immunofluorescence labeling and confocal microscopy were used to measure the distribution of Kv3.1b-ir, non-PV-ir, non-GABA-ir neurons across cortical depth in V1, and to determine whether, like the Meynert cells, other Kv3.1b-ir excitatory neurons were also SMI-32-ir pyramidal neurons. We found that Kv3.1b-ir, non-PV-ir, non-GABA-ir neurons were most prevalent in the M pathway-associated layers 4 Cα and 4B. GABAergic neurons accounted for a smaller fraction (11%) of the total neuronal population across layers 1-6 than has previously been reported. Of Kv3.1b-ir neurons, PV expression reliably indicated GABA expression. Kv3.1b-ir, non-PV-ir neurons varied in SMI-32 coimmunoreactivity. The results suggest the existence of a heterogeneous population of excitatory neurons in macaque V1 with the potential for sustained high firing rates, and these neurons were particularly abundant in layers 4B and 4 Cα.

Fast and robust active neuron segmentation in two-photon calcium imaging using spatiotemporal deep learning

Calcium imaging records large-scale neuronal activity with cellular resolution in vivo. Automated, fast, and reliable active neuron segmentation is a critical step in the analysis workflow of utilizing neuronal signals in real-time behavioral studies for discovery of neuronal coding properties. Here, to exploit the full spatiotemporal information in two-photon calcium imaging movies, we propose a 3D convolutional neural network to identify and segment active neurons. By utilizing a variety of two-photon microscopy datasets, we show that our method outperforms state-of-the-art techniques and is on a par with manual segmentation. Furthermore, we demonstrate that the network trained on data recorded at a specific cortical layer can be used to accurately segment active neurons from another layer with different neuron density. Finally, our work documents significant tabulation flaws in one of the most cited and active online scientific challenges in neuron segmentation. As our computationally fast method is an invaluable tool for a large spectrum of real-time optogenetic experiments, we have made our open-source software and carefully annotated dataset freely available online.

Spontaneous behaviors drive multidimensional, brainwide activity

Neuronal populations in sensory cortex produce variable responses to sensory stimuli and exhibit intricate spontaneous activity even without external sensory input. Cortical variability and spontaneous activity have been variously proposed to represent random noise, recall of prior experience, or encoding of ongoing behavioral and cognitive variables. Recording more than 10,000 neurons in mouse visual cortex, we observed that spontaneous activity reliably encoded a high-dimensional latent state, which was partially related to the mouse's ongoing behavior and was represented not just in visual cortex but also across the forebrain. Sensory inputs did not interrupt this ongoing signal but added onto it a representation of external stimuli in orthogonal dimensions. Thus, visual cortical population activity, despite its apparently noisy structure, reliably encodes an orthogonal fusion of sensory and multidimensional behavioral information.

Neuromodulatory control of localized dendritic spiking in critical period cortex

Sensory experience in early postnatal life, during so-called critical periods, restructures neural circuitry to enhance information processing1. Why the cortex is susceptible to sensory instruction in early life and why this susceptibility wanes with age are unclear. Here we define a developmentally restricted engagement of inhibitory circuitry that shapes localized dendritic activity and is needed for vision to drive the emergence of binocular visual responses in the mouse primary visual cortex. We find that at the peak of the critical period for binocular plasticity, acetylcholine released from the basal forebrain during periods of heightened arousal directly excites somatostatin (SST)-expressing interneurons. Their inhibition of pyramidal cell dendrites and of fast-spiking, parvalbumin-expressing interneurons enhances branch-specific dendritic responses and somatic spike rates within pyramidal cells. By adulthood, this cholinergic sensitivity is lost, and compartmentalized dendritic responses are absent but can be re-instated by optogenetic activation of SST cells. Conversely, suppressing SST cell activity during the critical period prevents the normal development of binocular receptive fields by impairing the maturation of ipsilateral eye inputs. This transient cholinergic modulation of SST cells, therefore, seems to orchestrate two features of neural plasticity-somatic disinhibition and compartmentalized dendritic spiking. Loss of this modulation may contribute to critical period closure.

Stimulus complexity shapes response correlations in primary visual cortex

Spike count correlations (SCCs) are ubiquitous in sensory cortices, are characterized by rich structure, and arise from structured internal dynamics. However, most theories of visual perception treat contributions of neurons to the representation of stimuli independently and focus on mean responses. Here, we argue that, in a functional model of visual perception, featuring probabilistic inference over a hierarchy of features, inferences about high-level features modulate inferences about low-level features ultimately introducing structured internal dynamics and patterns in SCCs. Specifically, high-level inferences for complex stimuli establish the local context in which neurons in the primary visual cortex (V1) interpret stimuli. Since the local context differentially affects multiple neurons, this conjecture predicts specific modulations in the fine structure of SCCs as stimulus identity and, more importantly, stimulus complexity varies. We designed experiments with natural and synthetic stimuli to measure the fine structure of SCCs in V1 of awake behaving macaques and assessed their dependence on stimulus identity and stimulus statistics. We show that the fine structure of SCCs is specific to the identity of natural stimuli and changes in SCCs are independent of changes in response mean. Critically, we demonstrate that stimulus specificity of SCCs in V1 can be directly manipulated by altering the amount of high-order structure in synthetic stimuli. Finally, we show that simple phenomenological models of V1 activity cannot account for the observed SCC patterns and conclude that the stimulus dependence of SCCs is a natural consequence of structured internal dynamics in a hierarchical probabilistic model of natural images.

Layer-Specific Physiological Features and Interlaminar Interactions in the Primary Visual Cortex of the Mouse

The relationship between mesoscopic local field potentials (LFPs) and single-neuron firing in the multi-layered neocortex is poorly understood. Simultaneous recordings from all layers in the primary visual cortex (V1) of the behaving mouse revealed functionally defined layers in V1. The depth of maximum spike power and sink-source distributions of LFPs provided consistent laminar landmarks across animals. Coherence of gamma oscillations (30-100 Hz) and spike-LFP coupling identified six physiological layers and further sublayers. Firing rates, burstiness, and other electrophysiological features of neurons displayed unique layer and brain state dependence. Spike transmission strength from layer 2/3 cells to layer 5 pyramidal cells and interneurons was stronger during waking compared with non-REM sleep but stronger during non-REM sleep among deep-layer excitatory neurons. A subset of deep-layer neurons was active exclusively in the DOWN state of non-REM sleep. These results bridge mesoscopic LFPs and single-neuron interactions with laminar structure in V1.

Mechanisms of Spatiotemporal Selectivity in Cortical Area MT

Cortical sensory neurons are characterized by selectivity to stimulation. This selectivity was originally viewed as a part of the fundamental "receptive field" characteristic of neurons. This view was later challenged by evidence that receptive fields are modulated by stimuli outside of the classical receptive field. Here, we show that even this modified view of selectivity needs revision. We measured spatial frequency selectivity of neurons in cortical area MT of alert monkeys and found that their selectivity strongly depends on luminance contrast, shifting to higher spatial frequencies as contrast increases. The changes of preferred spatial frequency are large at low temporal frequency, and they decrease monotonically as temporal frequency increases. That is, even interactions among basic stimulus dimensions of luminance contrast, spatial frequency, and temporal frequency strongly influence neuronal selectivity. This dynamic nature of neuronal selectivity is inconsistent with the notion of stimulus preference as a stable characteristic of cortical neurons.

Synapse-Selective Control of Cortical Maturation and Plasticity by Parvalbumin-Autonomous Action of SynCAM 1

Cortical plasticity peaks early in life and tapers in adulthood, as exemplified in the primary visual cortex (V1), wherein brief loss of vision in one eye reduces cortical responses to inputs from that eye during the critical period but not in adulthood. The synaptic locus of cortical plasticity and the cell-autonomous synaptic factors determining critical periods remain unclear. We here demonstrate that the immunoglobulin protein Synaptic Cell Adhesion Molecule 1 (SynCAM 1/Cadm1) is regulated by visual experience and limits V1 plasticity. Loss of SynCAM 1 selectively reduces the number of thalamocortical inputs onto parvalbumin (PV+) interneurons, impairing the maturation of feedforward inhibition in V1. SynCAM 1 acts in PV+ interneurons to actively restrict cortical plasticity, and brief PV+-specific knockdown of SynCAM 1 in adult visual cortex restores juvenile-like plasticity. These results identify a synapse-specific, cell-autonomous mechanism for thalamocortical visual circuit maturation and closure of the visual critical period.

Deep Two-Photon Imaging In Vivo with a Red-Shifted Calcium Indicator

Two-photon calcium imaging became in recent years a very popular method for the functional analysis of neural cell populations on a single-cell level in anesthetized or awake behaving animals. Scientific insights about single-cell processing of sensory information but also analyses of higher cognitive functions in healthy or diseased states became thereby feasible. However, two-photon imaging is generally limited to depths of a few hundred micrometers when recording from densely labeled cell populations. Therefore, such recordings are often restricted to the superficial layers 1-3 of the mouse cortex, whereas the deep cell layers 4-6 are hardly accessible with standard two-photon imaging. Here, we provide a protocol for deep two-photon calcium imaging, which allows imaging of neuronal circuits with single-cell resolution in all cortical layers of the mouse primary cortex. This technique can be readily applied to other species. The method includes a reduction of excitation light scattering by the use of a red-shifted calcium indicator and the minimization of background fluorescence by visually guided local application of the fluorescent dye. The technique is similar to previously published protocols for in vivo two-photon calcium imaging with synthetic calcium dyes (Stosiek et al. Proc Natl Acad Sci U S A 100:7319-7324, 2003). Hence, only minor changes of a generic two-photon setup and some adaptations of the experimental procedures are required.

Updating the picture of layer 2/3 VIP-expressing interneuron function in the mouse cerebral cortex

For years, interneurons expressing vasoactive intestinal peptide (VIP) interneurons and their function within the neocortex have been shrouded in mystery. Their relatively small size and minimal representation in the cortex have made investigation difficult. Due to their service role performed in co‑operation with glia and blood vessels to supply energy during neuronal activation in the brain, the contribution of VIP interneurons to local neuronal circuit function was not appreciated. VIP interneurons in the neocortex account for roughly 12% of all interneurons. They have been described as a subgroup of the third largest population of 5-hydroxytryptamine 3a (5HT3a) receptor‑expressing interneurons, non‑overlapping with interneuron populations expressing parvalbumin (PV) or somatostatin (SST). However, it was recently shown that only half of VIP interneurons display a 5HT3a receptor response and a subset of VIP interneurons in visual cortex co‑express SST. Over the last several years, due to new technical advancements, many facts have emerged relating to VIP interneuron phylogenetic origin, operational mechanisms within local circuits and functional significance. Some of these discoveries have dramatically shifted the perception of VIP interneurons. This review focuses on the function of the VIP interneurons residing in layer 2/3 of the mouse neocortex.

Faster processing of moving compared with flashed bars in awake macaque V1 provides a neural correlate of the flash lag illusion

When the brain has determined the position of a moving object, because of anatomical and processing delays the object will have already moved to a new location. Given the statistical regularities present in natural motion, the brain may have acquired compensatory mechanisms to minimize the mismatch between the perceived and real positions of moving objects. A well-known visual illusion-the flash lag effect-points toward such a possibility. Although many psychophysical models have been suggested to explain this illusion, their predictions have not been tested at the neural level, particularly in a species of animal known to perceive the illusion. To this end, we recorded neural responses to flashed and moving bars from primary visual cortex (V1) of awake, fixating macaque monkeys. We found that the response latency to moving bars of varying speed, motion direction, and luminance was shorter than that to flashes, in a manner that is consistent with psychophysical results. At the level of V1, our results support the differential latency model positing that flashed and moving bars have different latencies. As we found a neural correlate of the illusion in passively fixating monkeys, our results also suggest that judging the instantaneous position of the moving bar at the time of flash-as required by the postdiction/motion-biasing model-may not be necessary for observing a neural correlate of the illusion. Our results also suggest that the brain may have evolved mechanisms to process moving stimuli faster and closer to real time compared with briefly appearing stationary stimuli. NEW & NOTEWORTHY We report several observations in awake macaque V1 that provide support for the differential latency model of the flash lag illusion. We find that the equal latency of flash and moving stimuli as assumed by motion integration/postdiction models does not hold in V1. We show that in macaque V1, motion processing latency depends on stimulus luminance, speed and motion direction in a manner consistent with several psychophysical properties of the flash lag illusion.

Neuronal population mechanisms of lightness perception

The way that humans and animals perceive the lightness of an object depends on its physical luminance as well as its surrounding context. While neuronal responses throughout the visual pathway are modulated by context, the relationship between neuronal responses and lightness perception is poorly understood. We searched for a neuronal mechanism of lightness by recording responses of neuronal populations in monkey primary visual cortex (V1) and area V4 to stimuli that produce a lightness illusion in humans, in which the lightness of a disk depends on the context in which it is embedded. We found that the way individual units encode the luminance (or equivalently for our stimuli, contrast) of the disk and its context is extremely heterogeneous. This motivated us to ask whether the population representation in either V1 or V4 satisfies three criteria: 1) disk luminance is represented with high fidelity, 2) the context surrounding the disk is also represented, and 3) the representations of disk luminance and context interact to create a representation of lightness that depends on these factors in a manner consistent with human psychophysical judgments of disk lightness. We found that populations of units in both V1 and V4 fulfill the first two criteria but that we cannot conclude that the two types of information in either area interact in a manner that clearly predicts human psychophysical measurements: the interpretation of our population measurements depends on how subsequent areas read out lightness from the population responses. NEW & NOTEWORTHY A core question in visual neuroscience is how the brain extracts stable representations of object properties from the retinal image. We searched for a neuronal mechanism of lightness perception by determining whether the responses of neuronal populations in primary visual cortex and area V4 could account for a lightness illusion measured using human psychophysics. Our results suggest that comparing psychophysics with population recordings will yield insight into neuronal mechanisms underlying a variety of perceptual phenomena.

Isoflurane and ketamine differentially influence spontaneous and evoked laminar electrophysiology in mouse V1

General anesthesia is ubiquitous in research and medicine, yet although the molecular mechanisms of anesthetics are well characterized, their ultimate influence on cortical electrophysiology remains unclear. Moreover, the influence that different anesthetics have on sensory cortexes at neuronal and ensemble scales is mostly unknown and represents an important gap in knowledge that has widespread relevance for neural sciences. To address this knowledge gap, this work explored the effects of isoflurane and ketamine/xylazine, two widely used anesthetic paradigms, on electrophysiological behavior in mouse primary visual cortex. First, multiunit activity and local field potentials were examined to understand how each anesthetic influences spontaneous activity. Then, the interlaminar relationships between populations of neurons at different cortical depths were studied to assess whether anesthetics influenced resting-state functional connectivity. Lastly, the spatiotemporal dynamics of visually evoked multiunit and local field potentials were examined to determine how each anesthetic alters communication of visual information. We found that isoflurane enhanced the rhythmicity of spontaneous ensemble activity at 10-40 Hz, which coincided with large increases in coherence between layer IV with superficial and deep layers. Ketamine preferentially increased local field potential power from 2 to 4 Hz, and the largest increases in coherence were observed between superficial and deep layers. Visually evoked responses across layers were diminished under isoflurane, and enhanced under ketamine anesthesia. These findings demonstrate that isoflurane and ketamine anesthesia differentially impact sensory processing in V1. NEW & NOTEWORTHY We directly compared electrophysiological responses in awake and anesthetized (isoflurane or ketamine) mice. We also proposed a method for quantifying and visualizing highly variable, evoked multiunit activity. Lastly, we observed distinct oscillatory responses to stimulus onset and offset in awake and isoflurane-anesthetized mice.

Micro-Coil Design Influences the Spatial Extent of Responses to Intracortical Magnetic Stimulation

OBJECTIVE

Electrical stimulation via cortically implanted electrodes has been proposed to treat a wide range of neurological disorders. Effectiveness has been limited, however, in part due to the inability of conventional electrodes to activate specific types of neurons while avoiding other types. Recent demonstrations that magnetic stimulation from a micro-coil can selectively activate pyramidal neurons (PNs) while avoiding passing axons suggest the possibility that such an approach can overcome some this limitation and here we use computer simulations to explore how the micro-coil design influences the selectivity with which neurons are activated.

METHODS

A computational model was developed to compare the selectivity of magnetic stimulation induced by rectangular-, V-, and W-shaped coil designs. The more promising designs (V- and W-shapes) were fabricated for use in electrophysiological experiments including in vitro patch-clamp recording and calcium imaging (GCaMP6f) of mouse brain slices.

RESULTS

Both V- and W-shaped coils reliably activated layer 5 (L5) PNs but V-coils were more effective while W-coils were more selective. Activation thresholds with double-loop coils were approximately one-half those of single-loop coils. Calcium imaging revealed that both V- and W-coils better confine activation than electrodes.

CONCLUSION

Individual design features can influence both the strength as well as the selectivity of micro-coils and can be accurately predicted by computer simulations.

SIGNIFICANCE

Our results show that how coil design influences the response of cortical neurons to stimulation and are an important step toward the development of next-generation cortical prostheses.

Unidirectional monosynaptic connections from auditory areas to the primary visual cortex in the marmoset monkey

Until the late twentieth century, it was believed that different sensory modalities were processed by largely independent pathways in the primate cortex, with cross-modal integration only occurring in specialized polysensory areas. This model was challenged by the finding that the peripheral representation of the primary visual cortex (V1) receives monosynaptic connections from areas of the auditory cortex in the macaque. However, auditory projections to V1 have not been reported in other primates. We investigated the existence of direct interconnections between V1 and auditory areas in the marmoset, a New World monkey. Labelled neurons in auditory cortex were observed following 4 out of 10 retrograde tracer injections involving V1. These projections to V1 originated in the caudal subdivisions of auditory cortex (primary auditory cortex, caudal belt and parabelt areas), and targeted parts of V1 that represent parafoveal and peripheral vision. Injections near the representation of the vertical meridian of the visual field labelled few or no cells in auditory cortex. We also placed 8 retrograde tracer injections involving core, belt and parabelt auditory areas, none of which revealed direct projections from V1. These results confirm the existence of a direct, nonreciprocal projection from auditory areas to V1 in a different primate species, which has evolved separately from the macaque for over 30 million years. The essential similarity of these observations between marmoset and macaque indicate that early-stage audiovisual integration is a shared characteristic of primate sensory processing.

Colour Constancy Beyond the Classical Receptive Field

The problem of removing illuminant variations to preserve the colours of objects (colour constancy) has already been solved by the human brain using mechanisms that rely largely on centre-surround computations of local contrast. In this paper we adopt some of these biological solutions described by long known physiological findings into a simple, fully automatic, functional model (termed Adaptive Surround Modulation or ASM). In ASM, the size of a visual neuron's receptive field (RF) as well as the relationship with its surround varies according to the local contrast within the stimulus, which in turn determines the nature of the centre-surround normalisation of cortical neurons higher up in the processing chain. We modelled colour constancy by means of two overlapping asymmetric Gaussian kernels whose sizes are adapted based on the contrast of the surround pixels, resembling the change of RF size. We simulated the contrast-dependent surround modulation by weighting the contribution of each Gaussian according to the centre-surround contrast. In the end, we obtained an estimation of the illuminant from the set of the most activated RFs' outputs. Our results on three single-illuminant and one multi-illuminant benchmark datasets show that ASM is highly competitive against the state-of-the-art and it even outperforms learning-based algorithms in one case. Moreover, the robustness of our model is more tangible if we consider that our results were obtained using the same parameters for all datasets, that is, mimicking how the human visual system operates. These results suggest a dynamical adaptation mechanisms contribute to achieving higher accuracy in computational colour constancy.

Robust nanoscopy of a synaptic protein in living mice by organic-fluorophore labeling

Extending superresolution fluorescence microscopy to living animals has remained a challenging frontier ever since the first demonstration of STED (stimulated emission depletion) nanoscopy in the mouse visual cortex. The use of fluorescent proteins (FPs) in in vivo STED analyses has been limiting available fluorescence photon budgets and attainable image contrasts, in particular for far-red FPs. This has so far precluded the definition of subtle details in protein arrangements at sufficient signal-to-noise ratio. Furthermore, imaging with longer wavelengths holds promise for reducing photostress. Here, we demonstrate that a strategy based on enzymatic self-labeling of the HaloTag fusion protein by high-performance synthetic fluorophore labels provides a robust avenue to superior in vivo analysis with STED nanoscopy in the far-red spectral range. We illustrate our approach by mapping the nanoscale distributions of the abundant scaffolding protein PSD95 at the postsynaptic membrane of excitatory synapses in living mice. With silicon-rhodamine as the reporter fluorophore, we present imaging with high contrast and low background down to ∼70-nm lateral resolution in the visual cortex at ≤25-µm depth. This approach allowed us to identify and characterize the diversity of PSD95 scaffolds in vivo. Besides small round/ovoid shapes, a substantial fraction of scaffolds exhibited a much more complex spatial organization. This highly inhomogeneous, spatially extended PSD95 distribution within the disk-like postsynaptic density, featuring intricate perforations, has not been highlighted in cell- or tissue-culture experiments. Importantly, covisualization of the corresponding spine morphologies enabled us to contextualize the diverse PSD95 patterns within synapses of different orientations and sizes.

Biologically Inspired Hierarchical Contour Detection with Surround Modulation and Neural Connection

Contour is a very important feature in biological visual cognition and has been extensively investigated as a fundamental vision problem. In connection with the limitations of conventional models in detecting image contours in complex scenes, a hierarchical image contour extraction method is proposed based on the biological vision mechanism that draws on the perceptual characteristics of the early vision for features such as edges, shapes, and colours. By simulating the information processing mechanisms of the cells’ receptive fields in the early stages of the biological visual system, we put forward a computational model that combines feedforward, lateral, and feedback neural connections to decode and obtain the image contours. Our model simulations and their results show that the established hierarchical contour detection model can adequately fit the characteristics of the biological experiment, quickly and effectively detect the salient contours in complex scenes, and better suppress the unwanted textures.

Bidirectional encoding of motion contrast in the mouse superior colliculus

Detection of salient objects in the visual scene is a vital aspect of an animal's interactions with its environment. Here, we show that neurons in the mouse superior colliculus (SC) encode visual saliency by detecting motion contrast between stimulus center and surround. Excitatory neurons in the most superficial lamina of the SC are contextually modulated, monotonically increasing their response from suppression by the same-direction surround to maximal potentiation by an oppositely-moving surround. The degree of this potentiation declines with depth in the SC. Inhibitory neurons are suppressed by any surround at all depths. These response modulations in both neuronal populations are much more prominent to direction contrast than to phase, temporal frequency, or static orientation contrast, suggesting feature-specific saliency encoding in the mouse SC. Together, our findings provide evidence supporting locally generated feature representations in the SC, and lay the foundations towards a mechanistic and evolutionary understanding of their emergence.

Applications of STED fluorescence nanoscopy in unravelling nanoscale structure and dynamics of biological systems

Fluorescence microscopy, especially confocal microscopy, has revolutionized the field of biological imaging. Breaking the optical diffraction barrier of conventional light microscopy, through the advent of super-resolution microscopy, has ushered in the potential for a second revolution through unprecedented insight into nanoscale structure and dynamics in biological systems. Stimulated emission depletion (STED) microscopy is one such super-resolution microscopy technique which provides real-time enhanced-resolution imaging capabilities. In addition, it can be easily integrated with well-established fluorescence-based techniques such as fluorescence correlation spectroscopy (FCS) in order to capture the structure of cellular membranes at the nanoscale with high temporal resolution. In this review, we discuss the theory of STED and different modalities of operation in order to achieve the best resolution. Various applications of this technique in cell imaging, especially that of neuronal cell imaging, are discussed as well as examples of application of STED imaging in unravelling structure formation on biological membranes. Finally, we have discussed examples from some of our recent studies on nanoscale structure and dynamics of lipids in model membranes, due to interaction with proteins, as revealed by combination of STED and FCS techniques.

Overproduction of Neurons Is Correlated with Enhanced Cortical Ensembles and Increased Perceptual Discrimination

Brains vary greatly in neuronal number and density, even across individuals within the same species, yet it remains unclear whether such variation leads to differences in brain function or behavior. By imaging cortical activity of a mouse model in which neuronal production is moderately enhanced in utero, we find that animals with more cortical neurons also develop enhanced functional correlations and more distinct neuronal ensembles in primary visual cortex. These mice also have sharper orientation discrimination in their visual behavior. These results unveil a correlation between neuronal ensembles and behavior and suggest that neuronal number is linked to functional modularity and perceptual discrimination of visual cortex. By experimentally linking differences in neuronal number and behavior, our findings could help explain how evolutionary and developmental variability of individual and species brain size may lead to perceptual and cognitive differences.

Potassium channels contribute to activity-dependent regulation of dendritic inhibition

GABAergic inhibition plays a critical role in the regulation of neuronal activity. In the neocortex, inhibitory interneurons that target the dendrites of pyramidal cells influence both electrical and biochemical postsynaptic signaling. Voltage-gated ion channels strongly shape dendritic excitability and the integration of excitatory inputs, but their contribution to GABAergic signaling is less well understood. By combining 2-photon calcium imaging and focal GABA uncaging, we show that voltage-gated potassium channels normally suppress the GABAergic inhibition of calcium signals evoked by back-propagating action potentials in dendritic spines and shafts of cortical pyramidal neurons. Moreover, the voltage-dependent inactivation of these channels leads to enhancement of dendritic calcium inhibition following somatic spiking. Computational modeling reveals that the enhancement of calcium inhibition involves an increase in action potential depolarization coupled with the nonlinear relationship between membrane voltage and calcium channel activation. Overall, our findings highlight the interaction between intrinsic and synaptic properties and reveal a novel mechanism for the activity-dependent regulation of GABAergic inhibition.

Gamma and infra-slow oscillations shape neuronal firing in the rat subcortical visual system

KEY POINTS

Neuronal oscillations observed in sensory systems are physiological carriers of information about stimulus features. Rhythm in the infra-slow range, originating from the retina, was previously found in the firing of subcortical visual system nuclei involved in both image and non-image forming functions. The present study shows that the firing of neurons in the lateral geniculate nucleus is also governed by gamma oscillation (∼35 Hz) time-locked to high phase of infra-slow rhythm that codes the intensity of transient light stimulation. We show that both physiological rhythms are synchronized within and between ipsilateral nuclei of the subcortical visual system and are dependent on retinal activity. The present study shows that neurophysiological oscillations characterized by various frequencies not only coexist in the subcortical visual system, but also are subjected to complex interference and synchronization processes.

ABSTRACT

The physiological function of rhythmic firing in the neuronal networks of sensory systems has been linked with information coding. Also, neuronal oscillations in different frequency bands often change as a signature of brain state or sensory processing. Infra-slow oscillation (ISO) in the neuronal firing dependent on the retinal network has been described previously in the structures of the subcortical visual system. In the present study, we show for the first time that firing of ISO neurons in the lateral geniculate nucleus is also characterized by a harmonic discharge pattern (i.e. action potentials are separated by the intervals governed by fundamental frequency in the gamma range: ∼35 Hz). A similar phenomenon was recently described in the suprachiasmatic nuclei of the hypothalamus: the master biological clock. We found that both gamma and ISO rhythms were synchronized within and between ipsilateral nuclei of the subcortical visual system and were dependent on the retinal activity of the contralateral eye. These oscillatory patterns were differentially influenced by transient and prolonged light stimulation with respect to both frequency change direction and sustainability. The results of the present study show that the firing pattern of neurons in the subcortical visual system is shaped by oscillations from infra-slow and gamma frequency bands that are plausibly generated by the retinal network. Additionally, the results demonstrate that both rhythms are not a distinctive feature of image or non-image forming visual systems but, instead, they comprise two channels carrying distinctive properties of photic information.

Experience-dependent MeCP2 expression in the excitatory cells of mouse visual thalamus

Loss or gain of copy number of the gene encoding the transcription factor methyl-CpG-binding protein 2 (MeCP2) leads to neurodevelopmental disorders (Rett and MeCP2 duplication syndrome), indicating that precisely regulated MeCP2 expression during development is critical for mental health. Consistent with this idea, MeCP2 null mutants exhibit synaptic regression in the dorsal lateral geniculate nucleus (dLGN), the visual relay center in the thalamus, a phenotype resembling that of animals reared in the dark during the visual sensitive period. It remains unclear how MeCP2 expression is regulated during circuit formation and maturation, especially in excitatory and inhibitory populations of neurons. We found that, concomitant with the initiation of the dark-rearing sensitive period, MeCP2 protein levels were elevated in glutamatergic but not GABAergic neurons of the dLGN. Moreover, MeCP2 expression in glutamatergic populations was selectively reduced by dark-rearing. Therefore, we propose that visual experience-dependent MeCP2 induction in glutamatergic populations is essential for synaptic maturation within the dLGN.

Rem2 stabilizes intrinsic excitability and spontaneous firing in visual circuits

Sensory experience plays an important role in shaping neural circuitry by affecting the synaptic connectivity and intrinsic properties of individual neurons. Identifying the molecular players responsible for converting external stimuli into altered neuronal output remains a crucial step in understanding experience-dependent plasticity and circuit function. Here, we investigate the role of the activity-regulated, non-canonical Ras-like GTPase Rem2 in visual circuit plasticity. We demonstrate that Rem2-/- mice fail to exhibit normal ocular dominance plasticity during the critical period. At the cellular level, our data establish a cell-autonomous role for Rem2 in regulating intrinsic excitability of layer 2/3 pyramidal neurons, prior to changes in synaptic function. Consistent with these findings, both in vitro and in vivo recordings reveal increased spontaneous firing rates in the absence of Rem2. Taken together, our data demonstrate that Rem2 is a key molecule that regulates neuronal excitability and circuit function in the context of changing sensory experience.